A strategy that only works on certain currencies?

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nooby_mcnoob

I've got a swing trading strategy I've been working on that I hypothesized should work, and it seems to work in backtests on certain currencies. I've also traded it manually a few times to get a feel for it. The problem is that it doesn't work on all currencies and I don't know how to determine when to trade a currency with this strategy.

I began looking into it from the perspective of distributions of various price-related data and found what appears to be some sort of a relation between cumulative returns and this distribution.

In the images that follow, the left chart is cumulative return (dark blue) vs price (light blue). The right chart is a price-related distribution. To me, there appears to be some sort of a pattern with the currencies where it does work, and currencies where it doesn't.

I don't understand how to determine what really affects it.

Note: these results are without leverage. I would likely do 5x leverage in live trading.

Based on comments from others on this site, I am considering using deep learning to see if there is a way to back out a relationship that I don't know exists but I'm not sure I want to invest the time TBH.

What next steps would you take here?

USDJPY.png USDCHF.png USDCAD.png NZDUSD.png NZDJPY.png NZDCHF.png NZDCAD.png GBPUSD.png GBPNZD.png GBPJPY.png
 
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Pension_Admin said:
Cumulative return looks like an inflation line. Is there any asset that offer you better buy and hold return?
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Less concerned about that, as the returns shown don't account for leverage. I'm just trying to build a strategy that has no relation to the stock markets and can scale up and down.
 
Also, this sounds kind of retarded, but is it possible to transform the distribution from one that "doesn't work" into "one that does" and see if the same transformation on the price series makes a difference? Maybe...
 
Seems like the distributions that work less effectively are bimodal at the extremes of the values. If I do a transform on the underlying values to make them multimodal in a similar respect to the others and propagate that to the prices series, it may just work. But I'm pretty lazy... Is there a pandas function for this.
 
nooby_mcnoob said:
Less concerned about that, as the returns shown don't account for leverage. I'm just trying to build a strategy that has no relation to the stock markets and can scale up and down.
More...

The financing cost of leverage will have an impact on your return. Add that and see if you still got an upward equity slope.

For a strategy that has no relation to the stock market, you can try the all-weather portfolio. Ray has already build one long long time and ago.

PA
 
Pension_Admin said:
The financing cost of leverage will have an impact on your return. Add that and see if you still got an upward equity slope.

For a strategy that has no relation to the stock market, you can try the all-weather portfolio. Ray has already build one long long time and ago.

PA
More...

Already assumes cost of commissions and leverage (I just do 8x commission to model slippage, margin interest and commission).

Not surprising that a pension guy knows Dalio :)
 
Are you just assuming that 8x commissions is greater than all your real life costs combined or did you actually verify that this is true?

IB commission = 0.2bp => 8x commission = 1.6bp
The spread alone on some pairs can be multiples of that.
Financing costs can also be in the same order of magnitude.
 
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